{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "google",
   "metadata": {},
   "source": [
    "##### Copyright 2023 Google LLC."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apache",
   "metadata": {},
   "source": [
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "basename",
   "metadata": {},
   "source": [
    "# cvrptw_break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "link",
   "metadata": {},
   "source": [
    "<table align=\"left\">\n",
    "<td>\n",
    "<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/constraint_solver/cvrptw_break.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
    "</td>\n",
    "<td>\n",
    "<a href=\"https://github.com/google/or-tools/blob/main/ortools/constraint_solver/samples/cvrptw_break.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
    "</td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "doc",
   "metadata": {},
   "source": [
    "First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "install",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install ortools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "description",
   "metadata": {},
   "source": [
    "\n",
    "Capacitated Vehicle Routing Problem with Time Windows (CVRPTW).\n",
    "\n",
    "   This is a sample using the routing library python wrapper to solve a CVRPTW\n",
    "   problem.\n",
    "   A description of the problem can be found here:\n",
    "   http://en.wikipedia.org/wiki/Vehicle_routing_problem.\n",
    "\n",
    "   Distances are in meters and time in minutes.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "code",
   "metadata": {},
   "outputs": [],
   "source": [
    "import functools\n",
    "from ortools.constraint_solver import routing_enums_pb2\n",
    "from ortools.constraint_solver import pywrapcp\n",
    "\n",
    "\n",
    "def create_data_model():\n",
    "    \"\"\"Stores the data for the problem.\"\"\"\n",
    "    data = {}\n",
    "    # Locations in block unit\n",
    "    locations_ = [\n",
    "        # fmt: off\n",
    "      (4, 4),  # depot\n",
    "      (2, 0), (8, 0),  # locations to visit\n",
    "      (0, 1), (1, 1),\n",
    "      (5, 2), (7, 2),\n",
    "      (3, 3), (6, 3),\n",
    "      (5, 5), (8, 5),\n",
    "      (1, 6), (2, 6),\n",
    "      (3, 7), (6, 7),\n",
    "      (0, 8), (7, 8),\n",
    "        # fmt: on\n",
    "    ]\n",
    "    # Compute locations in meters using the block dimension defined as follow\n",
    "    # Manhattan average block: 750ft x 264ft -> 228m x 80m\n",
    "    # here we use: 114m x 80m city block\n",
    "    # src: https://nyti.ms/2GDoRIe \"NY Times: Know Your distance\"\n",
    "    data[\"locations\"] = [(l[0] * 114, l[1] * 80) for l in locations_]\n",
    "    data[\"numlocations_\"] = len(data[\"locations\"])\n",
    "    data[\"time_windows\"] = [\n",
    "        # fmt: off\n",
    "      (0, 0),  # depot\n",
    "      (75, 85), (75, 85),  #  1,  2\n",
    "      (60, 70), (45, 55),  #  3,  4\n",
    "      (0, 8), (50, 60),    #  5,  6\n",
    "      (0, 10), (10, 20),   #  7,  8\n",
    "      (0, 10), (75, 85),   #  9, 10\n",
    "      (85, 95), (5, 15),   # 11, 12\n",
    "      (15, 25), (10, 20),  # 13, 14\n",
    "      (45, 55), (30, 40),\n",
    "        # 15, 16\n",
    "        # fmt: on\n",
    "    ]\n",
    "    data[\"demands\"] = [\n",
    "        # fmt: off\n",
    "      0,     # depot\n",
    "      1, 1,  #  1,  2\n",
    "      2, 4,  #  3,  4\n",
    "      2, 4,  #  5,  6\n",
    "      8, 8,  #  7,  8\n",
    "      1, 2,  #  9, 10\n",
    "      1, 2,  # 11, 12\n",
    "      4, 4,  # 13, 14\n",
    "      8, 8,\n",
    "        # 15, 16\n",
    "        # fmt: on\n",
    "    ]\n",
    "    data[\"time_per_demand_unit\"] = 5  # 5 minutes/unit\n",
    "    data[\"num_vehicles\"] = 4\n",
    "    data[\"breaks\"] = [(2, False), (2, False), (2, False), (2, False)]\n",
    "    data[\"vehicle_capacity\"] = 15\n",
    "    data[\"vehicle_speed\"] = 83  # Travel speed: 5km/h converted in m/min\n",
    "    data[\"depot\"] = 0\n",
    "    return data\n",
    "\n",
    "\n",
    "def manhattan_distance(position_1, position_2):\n",
    "    \"\"\"Computes the Manhattan distance between two points.\"\"\"\n",
    "    return abs(position_1[0] - position_2[0]) + abs(position_1[1] - position_2[1])\n",
    "\n",
    "\n",
    "def create_distance_evaluator(data):\n",
    "    \"\"\"Creates callback to return distance between points.\"\"\"\n",
    "    distances_ = {}\n",
    "    # precompute distance between location to have distance callback in O(1)\n",
    "    for from_node in range(data[\"numlocations_\"]):\n",
    "        distances_[from_node] = {}\n",
    "        for to_node in range(data[\"numlocations_\"]):\n",
    "            if from_node == to_node:\n",
    "                distances_[from_node][to_node] = 0\n",
    "            else:\n",
    "                distances_[from_node][to_node] = manhattan_distance(\n",
    "                    data[\"locations\"][from_node], data[\"locations\"][to_node]\n",
    "                )\n",
    "\n",
    "    def distance_evaluator(manager, from_node, to_node):\n",
    "        \"\"\"Returns the manhattan distance between the two nodes.\"\"\"\n",
    "        return distances_[manager.IndexToNode(from_node)][manager.IndexToNode(to_node)]\n",
    "\n",
    "    return distance_evaluator\n",
    "\n",
    "\n",
    "def create_demand_evaluator(data):\n",
    "    \"\"\"Creates callback to get demands at each location.\"\"\"\n",
    "    demands_ = data[\"demands\"]\n",
    "\n",
    "    def demand_evaluator(manager, node):\n",
    "        \"\"\"Returns the demand of the current node.\"\"\"\n",
    "        return demands_[manager.IndexToNode(node)]\n",
    "\n",
    "    return demand_evaluator\n",
    "\n",
    "\n",
    "def add_capacity_constraints(routing, data, demand_evaluator_index):\n",
    "    \"\"\"Adds capacity constraint.\"\"\"\n",
    "    capacity = \"Capacity\"\n",
    "    routing.AddDimension(\n",
    "        demand_evaluator_index,\n",
    "        0,  # null capacity slack\n",
    "        data[\"vehicle_capacity\"],\n",
    "        True,  # start cumul to zero\n",
    "        capacity,\n",
    "    )\n",
    "\n",
    "\n",
    "def create_time_evaluator(data):\n",
    "    \"\"\"Creates callback to get total times between locations.\"\"\"\n",
    "\n",
    "    def service_time(data, node):\n",
    "        \"\"\"Gets the service time for the specified location.\"\"\"\n",
    "        return data[\"demands\"][node] * data[\"time_per_demand_unit\"]\n",
    "\n",
    "    def travel_time(data, from_node, to_node):\n",
    "        \"\"\"Gets the travel times between two locations.\"\"\"\n",
    "        if from_node == to_node:\n",
    "            travel_time = 0\n",
    "        else:\n",
    "            travel_time = (\n",
    "                manhattan_distance(\n",
    "                    data[\"locations\"][from_node], data[\"locations\"][to_node]\n",
    "                )\n",
    "                / data[\"vehicle_speed\"]\n",
    "            )\n",
    "        return travel_time\n",
    "\n",
    "    total_time_ = {}\n",
    "    # precompute total time to have time callback in O(1)\n",
    "    for from_node in range(data[\"numlocations_\"]):\n",
    "        total_time_[from_node] = {}\n",
    "        for to_node in range(data[\"numlocations_\"]):\n",
    "            if from_node == to_node:\n",
    "                total_time_[from_node][to_node] = 0\n",
    "            else:\n",
    "                total_time_[from_node][to_node] = int(\n",
    "                    service_time(data, from_node)\n",
    "                    + travel_time(data, from_node, to_node)\n",
    "                )\n",
    "\n",
    "    def time_evaluator(manager, from_node, to_node):\n",
    "        \"\"\"Returns the total time between the two nodes.\"\"\"\n",
    "        return total_time_[manager.IndexToNode(from_node)][manager.IndexToNode(to_node)]\n",
    "\n",
    "    return time_evaluator\n",
    "\n",
    "\n",
    "def add_time_window_constraints(routing, manager, data, time_evaluator_index):\n",
    "    \"\"\"Add Global Span constraint.\"\"\"\n",
    "    time = \"Time\"\n",
    "    horizon = 120\n",
    "    routing.AddDimension(\n",
    "        time_evaluator_index,\n",
    "        horizon,  # allow waiting time\n",
    "        horizon,  # maximum time per vehicle\n",
    "        False,  # don't force start cumul to zero\n",
    "        time,\n",
    "    )\n",
    "    time_dimension = routing.GetDimensionOrDie(time)\n",
    "    # Add time window constraints for each location except depot\n",
    "    # and 'copy' the slack var in the solution object (aka Assignment) to print it\n",
    "    for location_idx, time_window in enumerate(data[\"time_windows\"]):\n",
    "        if location_idx == data[\"depot\"]:\n",
    "            continue\n",
    "        index = manager.NodeToIndex(location_idx)\n",
    "        time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])\n",
    "        routing.AddToAssignment(time_dimension.SlackVar(index))\n",
    "    # Add time window constraints for each vehicle start node\n",
    "    # and 'copy' the slack var in the solution object (aka Assignment) to print it\n",
    "    for vehicle_id in range(data[\"num_vehicles\"]):\n",
    "        index = routing.Start(vehicle_id)\n",
    "        time_dimension.CumulVar(index).SetRange(\n",
    "            data[\"time_windows\"][0][0], data[\"time_windows\"][0][1]\n",
    "        )\n",
    "        routing.AddToAssignment(time_dimension.SlackVar(index))\n",
    "        # The time window at the end node was impliclty set in the time dimension\n",
    "        # definition to be [0, horizon].\n",
    "        # Warning: Slack var is not defined for vehicle end nodes and should not\n",
    "        # be added to the assignment.\n",
    "\n",
    "\n",
    "def print_solution(\n",
    "    data, manager, routing, assignment\n",
    "):  # pylint:disable=too-many-locals\n",
    "    \"\"\"Prints assignment on console.\"\"\"\n",
    "    print(f\"Objective: {assignment.ObjectiveValue()}\")\n",
    "\n",
    "    print(\"Breaks:\")\n",
    "    intervals = assignment.IntervalVarContainer()\n",
    "    for i in range(intervals.Size()):\n",
    "        brk = intervals.Element(i)\n",
    "        if brk.PerformedValue() == 1:\n",
    "            print(\n",
    "                f\"{brk.Var().Name()}:\"\n",
    "                f\" Start({brk.StartValue()}) Duration({brk.DurationValue()})\"\n",
    "            )\n",
    "        else:\n",
    "            print(f\"{brk.Var().Name()}: Unperformed\")\n",
    "\n",
    "    total_distance = 0\n",
    "    total_load = 0\n",
    "    total_time = 0\n",
    "    capacity_dimension = routing.GetDimensionOrDie(\"Capacity\")\n",
    "    time_dimension = routing.GetDimensionOrDie(\"Time\")\n",
    "    for vehicle_id in range(data[\"num_vehicles\"]):\n",
    "        index = routing.Start(vehicle_id)\n",
    "        plan_output = f\"Route for vehicle {vehicle_id}:\\n\"\n",
    "        distance = 0\n",
    "        while not routing.IsEnd(index):\n",
    "            load_var = capacity_dimension.CumulVar(index)\n",
    "            time_var = time_dimension.CumulVar(index)\n",
    "            slack_var = time_dimension.SlackVar(index)\n",
    "            node = manager.IndexToNode(index)\n",
    "            plan_output += (\n",
    "                f\" {node}\"\n",
    "                f\" Load({assignment.Value(load_var)})\"\n",
    "                f\" Time({assignment.Min(time_var)}, {assignment.Max(time_var)})\"\n",
    "                f\" Slack({assignment.Min(slack_var)}, {assignment.Max(slack_var)})\"\n",
    "                \" ->\"\n",
    "            )\n",
    "            previous_index = index\n",
    "            index = assignment.Value(routing.NextVar(index))\n",
    "            distance += routing.GetArcCostForVehicle(previous_index, index, vehicle_id)\n",
    "        load_var = capacity_dimension.CumulVar(index)\n",
    "        time_var = time_dimension.CumulVar(index)\n",
    "        node = manager.IndexToNode(index)\n",
    "        plan_output += (\n",
    "            f\" {node}\"\n",
    "            f\" Load({assignment.Value(load_var)})\"\n",
    "            f\" Time({assignment.Min(time_var)}, {assignment.Max(time_var)})\\n\"\n",
    "        )\n",
    "        plan_output += f\"Distance of the route: {distance}m\\n\"\n",
    "        plan_output += f\"Load of the route: {assignment.Value(load_var)}\\n\"\n",
    "        plan_output += f\"Time of the route: {assignment.Value(time_var)}\\n\"\n",
    "        print(plan_output)\n",
    "        total_distance += distance\n",
    "        total_load += assignment.Value(load_var)\n",
    "        total_time += assignment.Value(time_var)\n",
    "    print(f\"Total Distance of all routes: {total_distance}m\")\n",
    "    print(f\"Total Load of all routes: {total_load}\")\n",
    "    print(f\"Total Time of all routes: {total_time}min\")\n",
    "\n",
    "\n",
    "def main():\n",
    "    \"\"\"Entry point of the program.\"\"\"\n",
    "    # Instantiate the data problem.\n",
    "    data = create_data_model()\n",
    "\n",
    "    # Create the routing index manager\n",
    "    manager = pywrapcp.RoutingIndexManager(\n",
    "        data[\"numlocations_\"], data[\"num_vehicles\"], data[\"depot\"]\n",
    "    )\n",
    "\n",
    "    # Create Routing Model\n",
    "    routing = pywrapcp.RoutingModel(manager)\n",
    "\n",
    "    # Define weight of each edge\n",
    "    distance_evaluator_index = routing.RegisterTransitCallback(\n",
    "        functools.partial(create_distance_evaluator(data), manager)\n",
    "    )\n",
    "    routing.SetArcCostEvaluatorOfAllVehicles(distance_evaluator_index)\n",
    "\n",
    "    # Add Capacity constraint\n",
    "    demand_evaluator_index = routing.RegisterUnaryTransitCallback(\n",
    "        functools.partial(create_demand_evaluator(data), manager)\n",
    "    )\n",
    "    add_capacity_constraints(routing, data, demand_evaluator_index)\n",
    "\n",
    "    # Add Time Window constraint\n",
    "    time_evaluator_index = routing.RegisterTransitCallback(\n",
    "        functools.partial(create_time_evaluator(data), manager)\n",
    "    )\n",
    "    add_time_window_constraints(routing, manager, data, time_evaluator_index)\n",
    "\n",
    "    # Add breaks\n",
    "    time_dimension = routing.GetDimensionOrDie(\"Time\")\n",
    "    node_visit_transit = {}\n",
    "    for index in range(routing.Size()):\n",
    "        node = manager.IndexToNode(index)\n",
    "        node_visit_transit[index] = int(\n",
    "            data[\"demands\"][node] * data[\"time_per_demand_unit\"]\n",
    "        )\n",
    "\n",
    "    break_intervals = {}\n",
    "    for v in range(data[\"num_vehicles\"]):\n",
    "        vehicle_break = data[\"breaks\"][v]\n",
    "        break_intervals[v] = [\n",
    "            routing.solver().FixedDurationIntervalVar(\n",
    "                15, 100, vehicle_break[0], vehicle_break[1], f\"Break for vehicle {v}\"\n",
    "            )\n",
    "        ]\n",
    "        time_dimension.SetBreakIntervalsOfVehicle(\n",
    "            break_intervals[v], v, node_visit_transit.values()\n",
    "        )\n",
    "\n",
    "    # Setting first solution heuristic (cheapest addition).\n",
    "    search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
    "    search_parameters.first_solution_strategy = (\n",
    "        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC\n",
    "    )  # pylint: disable=no-member\n",
    "\n",
    "    # Solve the problem.\n",
    "    assignment = routing.SolveWithParameters(search_parameters)\n",
    "\n",
    "    # Print solution on console.\n",
    "    if assignment:\n",
    "        print_solution(data, manager, routing, assignment)\n",
    "    else:\n",
    "        print(\"No solution found!\")\n",
    "\n",
    "\n",
    "main()\n",
    "\n"
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}
